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October 21, 2008

Synthetic Telepathy and Better machine neuron connections

The Army has given a grant to researchers at University of California, Irvine, Carnegie Mellon University and the University of Maryland has two objectives.

The first is to compose a message using, as D'Zmura puts it, "that little voice in your head."

The second part is to send that message to a particular individual or object (like a radio), also just with the power of thought. Once the message reaches the recipient, it could be read as text or as a voice mail.


In a separate but related development movement was restored to paralyzed limbs in monkeys through artificial brain-muscle connections. The two projects could combine with the more robust brain and neuron connections helping to provide better signals for the synthetic telepathy work.

The group's approach is one of several lines of current neuroprosthetic research. Some investigators are using brain-computer interfaces to record signals from multiple neurons and convert those signals to control a robotic limb. Other researchers have delivered artificial stimulation directly to paralyzed arm muscles in order to drive arm movement—a technique called functional electrical stimulation (FES). The Fetz study is the first to combine a brain-computer interface with real-time control of FES.

Until now, brain-computer interfaces were designed to decode the activity of neurons known to be associated with movement of specific body parts. Here, the researchers discovered that any motor cortex cell, regardless of whether it had been previously associated with wrist movement, was capable of stimulating muscle activity. This finding greatly expands the potential number of neurons that could control signals for brain-computer interfaces and also illustrates the flexibility of the motor cortex.

The advantage of Moritz’s approach is that the signal from a single neuron can be interpreted by a much less powerful computer chip, perhaps one small and low-powered enough to implant into the animal’s — or a patient’s — body.

Moritz also suggests that his team’s approach could eventually control several muscles at once by electrically stimulating nerves in the spinal cord, rather than stimulating the muscles directly. Eventually the researchers hope to develop wireless electrodes that wouldn’t involve wires sticking out of the skull, Moritz says.

Clinical applications are still probably at least a decade away, according to Dr. Fetz. Better methods for recording cortical neurons and for controlling multiple muscles must be developed, along with implantable circuitry that could be used reliably and safely, he says.


Previous implants collect signals from large collections of neurons, and need complex software to process them into a clean output signal.

Moritz's system, though, uses only 12 moving electrodes – just 50 micrometres wide – to seek out and connect to just a single neuron. This produces a much simpler and tidier output signal.

After being inserted into the brain's motor cortex, the device can sense where the strongest signal is coming from, and move the electrodes towards it.

Piezoelectric motors can move the 12 electrodes in small 1-micrometre increments and will back off when necessary to avoid damaging nerve cells.







Commercial EEG headsets already exist that allow wearers to manipulate virtual objects by thought alone, noted Sajda, but thinking "move rock" is easier than, say, "Have everyone meet at Starbucks at 5:30."

One difficulty in composing specific messages is fundamental — EEGs are not very specific. They can only locate a signal to within about one to two centimeters. That's a large distance in the brain. In the brain's auditory cortex, for example, two centimeters is the difference between low notes and high notes, D'Zmura said.

Placing electrodes between the skull and the brain would offer more precise readings, but it is expensive and requires invasive surgery.

To work around this problem, the scientists need to gain a much better understanding of what words and phrases light up what brain sections. To create a detailed map of the brain scientists will also use functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG).

Each technology has its own strengths and weaknesses. EEGs detect brain activity only on the outer bulges of the brain's folds. MEGs read brain activity on the inner folds but are too large to put on your head. FMRIs detect brain activity more accurately than either but are heavy and expensive.

Of all three technologies EEG is the one currently cheap enough, light enough and fast enough for a mass market device.

The map generated by all three technologies will help the computer guess which word of phrase a person means when a part of the brain is lights up on the EEG. The idea is similar to how dictation software like Dragon NaturallySpeaking uses context to help determine which word you said.


FURTHER READING
Direct control of paralysed muscles by cortical neurons

A potential treatment for paralysis resulting from spinal cord injury is to route control signals from the brain around the injury by artificial connections. Such signals could then control electrical stimulation of muscles, thereby restoring volitional movement to paralysed limbs. In previously separate experiments, activity of motor cortex neurons related to actual or imagined movements has been used to control computer cursors and robotic arms and paralysed muscles have been activated by functional electrical stimulation. Here we show that Macaca nemestrina monkeys can directly control stimulation of muscles using the activity of neurons in the motor cortex, thereby restoring goal-directed movements to a transiently paralysed arm. Moreover, neurons could control functional stimulation equally well regardless of any previous association to movement, a finding that considerably expands the source of control signals for brain-machine interfaces. Monkeys learned to use these artificial connections from cortical cells to muscles to generate bidirectional wrist torques, and controlled multiple neuron–muscle pairs simultaneously. Such direct transforms from cortical activity to muscle stimulation could be implemented by autonomous electronic circuitry, creating a relatively natural neuroprosthesis. These results are the first demonstration that direct artificial connections between cortical cells and muscles can compensate for interrupted physiological pathways and restore volitional control of movement to paralysed limbs.


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